bioRxivBioinformaticsPreprint
IMMREP25: Unseen Peptides
Eve RichardsoniD, Yannick Jurriaan Maria AartsiD, John A. AltiniD, Coos A. B. BaakmaniD, Philip H BradleyiD, Binbin CheniD, Joakim Nøddeskov CliffordiD, Manjima DhariD, Danielle Diepenbroek, Ethan FastiD, Ragul GowthamaniD, Jieling HeiD, Vadim K KarnaukhoviD, Dario F. MarzellaiD, Pieter MeysmaniD, Morten NielseniD, Jonas Birkelund NilssoniD, Sebastian Nymann DeleuraniD, Farzaneh M. PariziiD, Aurélien PélissieriD, Brian G. PierceiD, María Rodríguez MartíneziD, Dona Roran A R, Shayana SaravanakumariD, Yanjun ShaoiD, , Bjoern PetersiD
Abstract
T cell receptors (TCRs) can bind to peptides presented by MHC molecules (pMHC) as a first step to trigger a T cell response. Reliable approaches to predict TCR:pMHC binding would have broad applications in clinical diagnostics, therapeutics, and the fundamental understanding of molecular interactions. IMMREP is a community organized series of prediction contests that asks participants to predict TCR:pMHC binding on unpublished datasets. Previous iterations in 2022 and 2023 showed multiple approaches can predict TCR-pMHC binding with significant accuracy (median AUC_0.1[≥]0.7) for peptides where experimental data is available ("seen" peptides). In contrast, models did not outperform random guessing for peptides that have no such data available ("unseen" peptides). Here we report on the results of IMMREP25, which focused solely on unseen peptides in order to evaluate the cutting edge of the field. We received 126 named submissions predicting the specificity of 1,000 TCRs against twenty unseen peptides restricted by one of two MHC molecules (HLA-A*02:01 and HLA-B*40:01). The best performing methods showed a macro-AUC_0.1 of 0.60, significantly better than random, demonstrating significant advances in the field. The top performing methods incorporated structural modeling into their approach, indicating that especially for unseen peptides, a structural understanding aids in the prediction of TCR:pMHC interactions. The results from this benchmark highlight the significant challenges remaining for TCR:pMHC predictions and will inform future method development.
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